• Journal of The Korean Digital Architecture Interior Association
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• v.13 no.4
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• pp.95-108
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• 2013

The purpose of this study is to analyze and to grasp Peter Calthorpe's urbanism through the process that is compared with various developments of urban design field for the preservation of global environment. From this study, Peter Calthorpe's urbanism for global environment is comprehended according to design stages. As a design goal, He seeks a green urbanism that puts emphasis on land use and transportation. As a urban planning, he devises urban footprint for the tool of evaluation and urban planning, and proposes five place types toward mixed-use development, and advocates Transect for eco-friendly land use. As a urban design, he devises urban network model for transportation network based on accessibility, and devises TOD and TOC model for preventing urban sprawl and mitigating carbon emissions, and advocates TND model for pedestrian-friendly space and community life. He makes importance of urban design. Because he thinks that integrative solution is required to global environment and urban design of integrative characteristic is suitable to preserve global environment. The results of this study are summarized as the followings: First, type classification of urbanism for the preservation of global environment and grasping purposes, methods, characteristics according to the types. Second, grasping characteristics and location of Peter Calthorpe's urbanism as a green urbanism. Third, proposing the direction of improvement for our urban planning and design.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.862-866
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• 2003

Traveling Salesman Problem(TSP) is a combinational optimization problem, Genetic Algorithm(GA) and Lin-Kernighan(LK) Heuristic［1］that is Local Search Heuristic are one of the most commonly used methods to resolve TSP. In this paper, we introduce ACS(Ant Colony System) Algorithm as another approach to solve TSP and propose a new pheromone updating method. ACS uses pheromone information between cities in the Process where many ants make a tour, and is a method to find a optimal solution through recursive tour creation process. At the stage of Global Updating of ACS method, it updates pheromone of edges belonging to global best tour of created all edge. But we perform once more pheromone update about created all edges before global updating rule of original ACS is applied. At this process, we use the frequency of occurrence of each edges to update pheromone. We could offer stochastic value by pheromone about each edges, giving all edges' occurrence frequency as weight about Pheromone. This finds an optimal solution faster than existing ACS algorithm and prevent a local optima using more edges in next time search.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.2
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• pp.129-134
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• 2008

In this paper, we carry out the simulation for an optimal solution of one-dimensional nonlinear photonic crystal structure using Genetic algorithm, and show the proposed method to apply for photonic transistors. Unlike a conventional steepest descent method for an optimization, the proposed method based on Genetic Algorithm has advantages for finding out excellent solutions without any analytic forms, which can easily apply to other applications. Also, as several solutions around global minimum solution can be obtained, it is very good optimization tool to give us the patterns about the optimal structure of a photonic crystal transistor. To design an all-optical filter transistor, Neural network algorithm is firstly performed for an initial design and then Genetic Algorithm is finally used to get the optimal solution. From the simulation of one-dimensional photonic crystal transistor, 27dB of the switching On/Off ratio is obtained.

• Journal of Chest Surgery
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• v.24 no.4
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• pp.331-337
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• 1991

Recent experimental work indicates latamoxef sodium used as a broadspectrum antibiotics generates oxygen-free radicals. The present study represents an attempt to investigate whether reperfusate containing Shiomarin[85% latamoxef sodium+15% mannitol] might decrease the post-ischemic recovery of cardiac function. In the investigation, twelve isolated rat hearts were subjected to 270 minutes of cold total global ischemia. After the cold total global ischemia, six hearts[KHB group] were reperfused with Krebs-Henseleit buffer solution and the other six hearts[LMS group] with Krebs-Henseleit buffer solution containing latamoxef sodium[200ug /L]. Postischemic recovery rate of heart rate, aortic systolic pressure, aortic flow, coronary flow and cardiac output at 20 minutes reperfusion was 100.66$\pm$10.38, 85.25$\pm$7.61, 78.95$\pm$6. 02, 78.85$\pm$8.86 and 79.11$\pm$6.54 percent respectively in the KHB group and 97.96$\pm$4.19, 87. 72$\pm$4.37, 81.74$\pm$6.80, 82.69$\pm$10.01 and 81.90$\pm$6.67 percent respectively in the LMS group. The hemodynamic data revealed no significant difference in the post-ischemic recovery rate of the two groups. This finding suggests that reperfusate containing Shiomarin[latamoxef sodium, 200ug /L] does not affect the cardiac functional recovery after cold total global ischemia.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.25 no.4
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• pp.173-195
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• 2021

A new implicit discontinuous Galerkin spectral element method (DGSEM) based on the first order hyperbolic system(FOHS) is presented for solving elliptic type partial different equations, such as the Poisson problems. By utilizing the idea of hyperbolic formulation of Nishikawa[1], the original Poisson equation was reformulated in the first-order hyperbolic system. Such hyperbolic system is solved implicitly by the collocation type DGSEM. The steady state solution in pseudo-time, which is the solution of the original Poisson problem, was obtained by the implicit solution of the global linear system. The optimal polynomial orders of 𝒪(𝒽^𝑝+1)) are obtained for both the solution and gradient variables from the test cases in 1D and 2D regular grids. Spectral accuracy of the solution and gradient variables are confirmed from all test cases of using the uniform grids in 2D.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.58-65
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• 2021

Meta-heuristic algorithms have been developed to efficiently solve difficult problems and obtain a global optimal solution. A common feature mimics phenomenon occurring in nature and reliably improves the solution through repetition. And at the same time, the probability is used to deviate from the regional optimal solution and approach the global optimal solution. This study compares the algorithm created based on the above common points with existed SA and HS to show advantages in time and accuracy of results. Existing algorithms have problems of low accuracy, high memory, long runtime, and ignorance. In a two-variable polynomial, the existing algorithms show that the memory increases and the accuracy decrease. In order to improve the accuracy, the new algorithm increases the number of initial inputs and increases the efficiency of the search by introducing a direction using vectors. And, in order to solve the optimization problem, the results of the last experiment were learned to show the learning effect in the next experiment. The new algorithm found a solution in a short time under the experimental conditions of long iteration counts using a two-variable polynomial and showed high accuracy. And, it shows that the learning effect is effective in repeated experiments.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1381-1393
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• 2011

In this paper, we consider two-species periodic Gilpin-Ayala competition system with delay and impulsive effect. By using some analysis methods, sufficient conditions for the permanence of the system are derived. Further, we give the conditions of the existence and global asymptotic stable of positive periodic solution.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.554-558
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• 2001

In this study, a hybrid method is used to search the pseudo-optimal solution for the I-dimentional nesting problem. This method is composed of the genetic algorithm for the global search and a simple heuristic one for the local search near the pseudo optimal solution. Several simulation results show that the hybrid method gives very satisfactory results.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.147-158
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• 1995

In this paper a face optimization algorithm is developed for solving the problem (P) of optimizing a linear function over the set of efficient solution of a bicriterion linear program. We show that problem (P) can arise in a variety of practical situations. Since the efficient set is in general a nonoconvex set, problem (P) can be classified as a global optimization problem. The algorithm for solving problem (P) is guaranteed to find an exact optimal or almost exact optimal solution for the problem in a finite number of iterations. The algorithm can be easily implemented using only linear programming method.

• Journal of applied mathematics & informatics
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• v.8 no.3
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• pp.721-729
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• 2001

We consider finite element methods applied to a class of Sobolev equations in $R^d$($d{\geq}1$). Global strong superconvergence, which only requires that partitions are quais-uniform, is investigated for the error between the approximate solution and the Ritz-Sobolev projection of the exact solution. Two order superconvervgence results are demonstrated in $W^{1,p}({\Omega})$ and $L_p({\Omega})$ for $2{\leq}p$＜${\infty}$.